Adaptive Output Consensus of Heterogeneous Multi-Agent System with Switching Topology

doi:10.16183/j.cnki.jsjtu.2024.221

Abstract

Abstract:

In this paper, a leader-model-follower matching-based distributed adaptive cooperative control scheme is developed by equivalenting abrupt changing topology to switching topology problem for uncertain heterogeneous multi-agent systems with abrupt changing communication topology to realize leader-follower output consensus. First, local output tracking error is proposed to transform the leader-follower global output consensus problem into the neighboring agents local output consensus problem. Then, the distributed nominal cooperative control design is performed with known system parameters to realize reference model-leader matching and follower-reference model matching, to ensure the leader-follower output consensus with abrupt changing communication topology. Afterwards, the distributed adaptive cooperative controller is studied to realize the asymptotic output tracking of the follower to the leader with unknown parameters under the abrupt change of communication topology. The designed control strategy can ensure the closed loop stabilization of the global agents as well as the leader-follower output consensus with switching topology without relying on global information. Finally, the effectiveness of the designed control scheme is verified by simulation.

Key words: heterogeneous multi-agent systems, output consensus, adaptive control, switching topology

CLC Number:

TP273

LIU Yu, WEN Liyan, JIANG Bin, MA Yajie, CUI Yukang. Adaptive Output Consensus of Heterogeneous Multi-Agent System with Switching Topology[J]. Journal of Shanghai Jiao Tong University, 2024, 58(11): 1805-1815.

Figures/Tables 4

References 31

[1]	GONG J, JIANG B, MA Y. Adaptive fault tolerant supervisory consensus control for nonlinear strict-feedback multiagent systems[C]//International Conference on Guidance, Navigation and Control. Singapore, Singapore: Springer, 2022: 1603-1703.
[2]	CHU H, CAI Y, ZHANG W. Consensus tracking for multi-agent systems with directed graph via distributed adaptive protocol[J]. Neurocomputing, 2015, 166: 8-13.
[3]	BAO G, MA L, YI X. Recent advances on cooperative control of heterogeneous multi-agent systems subject to constraints: A survey[J]. Systems Science & Control Engineering, 2022, 10(1): 539-551.
[4]	CANESE L, CARDARILLI G C, DI N L, et al. Multi-agent reinforcement learning: A review of challenges and applications[J]. Applied Sciences, 2021, 11(11): 1-25.
[5]	AMIRKHANI A, BARSHOOI A H. Consensus in multi-agent systems: A review[J]. Artificial Intelligence Review, 2022, 55(5): 3897-3935.
[6]	SKEIK O, LANZON A. Robust output consensus of homogeneous multi-agent systems with negative imaginary dynamics[J]. Automatica, 2020, 113: 108799.
[7]	BHATTACHARYYA S, PATRA S. Positive consensus of multi-agent systems with hierarchical control protocol[J]. Automatica, 2022, 139: 110191.
[8]	YU P, LIU K, LIU X, et al. Robust consensus tracking control of uncertain multi-agent systems with local disturbance rejection[J]. IEEE/CAA Journal of Automatica Sinica, 2023, 10(2): 427-438.
[9]	沈林成, 牛轶峰, 朱华勇. 多无人机自主协同控制理论与方法[M]. 北京: 国防工业出版社, 2013.
	SHEN Lincheng, NIU Yifeng, ZHU Huayong. Theories and methods of autonomous cooperative control for multiple UAVs[M]. Bejing: National Defense Industry Press, 2013.
[10]	HU D, VINCENT J L G, WANG T, et al. Multi-agent robotic system (MARS) for UAV-UGV path planning and automatic sensory data collection in cluttered environments[J]. Building and Environment, 2022, 221: 109349.
[11]	YAN B, SHI P, LIM C C. Robust formation control for nonlinear heterogeneous multiagent systems based on adaptive event-triggered strategy[J]. IEEE Transactions on Automation Science and Engineering, 2022, 19(4): 2788-2800.
[12]	YAO D, LI H, LU R, et al. Distributed sliding-mode tracking control of second-order nonlinear multiagent systems: An event-triggered approach[J]. IEEE Transactions on Cybernetics, 2020, 50(9): 3892-3902. doi: 10.1109/TCYB.2019.2963087 pmid: 31995513
[13]	ZHANG J, ZHANG H, LU Y, et al. Cooperative output regulation of heterogeneous linear multi-agent systems with edge-event triggered adaptive control under time-varying topologies[J]. Neural Computing and Applications, 2020, 32(19): 15573-15584.
[14]	WEN L, TAO G, YANG H, et al. Adaptive actuator failure compensation for possibly nonminimum-phase systems using control separation based LQ design[J]. IEEE Transactions on Automatic Control, 2018, 64(1): 143-158.
[15]	WEN L, TAO G, JIANG B, et al. Adaptive LQ control using reduced hamiltonian for continuous-time systems with unmatched input disturbances[J]. SIAM Journal on Control and Optimization, 2021, 59(5): 3625-3660.
[16]	HAN T, GUAN Z, XIAO B, et al. Bipartite average tracking for multi-agent systems with disturbances: Finite-time and fixed-time convergence[J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2021, 68(10): 4393-4402.
[17]	CAO W, LIU L, FENG G. Distributed adaptive output consensus of unknown heterogeneous non-minimum phase multi-agent systems[J]. IEEE/CAA Journal of Automatica Sinica, 2023, 10(4): 997-1008.
[18]	YANG R, LIU L, FENG G. Cooperative output tracking of unknown heterogeneous linear systems by distributed event-triggered adaptive control[J]. IEEE Transactions on Cybernetics, 2020, 52(1): 3-15.
[19]	马思迁, 董朝阳, 马鸣宇, 等. 基于自适应通信拓扑四旋翼无人机编队重构控制[J]. 北京航空航天大学学报, 2018, 44(4): 841-850.
	MA Siqian, DONG Chaoyang, MA Mingyu, et al. Formation reconfiguration control of quadrotor UAVs based on adaptive communication topology[J]. Journal of Beijing University of Aeronautics and Astronasutics, 2018, 44(4): 841-850.
[20]	BALDI S, YUAN S, PAOLO F. Output synchronization of unknown heterogeneous agents via distributed model reference adaptation[J]. IEEE Transactions on Control of Network Systems, 2018, 6(2): 515-525.
[21]	ROSA M R. Adaptive synchronization for heterogeneous multi-agent systems with switching topologies[J]. Machines, 2018, 6(1): 1-18.
[22]	SONG G, TAO G, TAN C. A distributed adaptive state feedback control scheme for output consensus of multi-agent systems[C]//Asian Control Conference. Piscataway, USA: IEEE, 2019: 1149-1154.
[23]	WEN L, TAO G, YANG H, et al. Aircraft turbulence compensation using adaptive multivariable disturbance rejection techniques[J]. Journal of Guidance, Control, and Dynamics, 2015, 38(5): 954-963.
[24]	TAO G. Adaptive control design and analysis[M]. New York, USA: John Wiley & Sons, 2003.
[25]	杨浩, 姜斌, 周东华. 互联系统容错控制的研究回顾与展望[J]. 自动化学报, 2017, 43(1): 9-19.
	YANG Hao, JIANG Bin, ZHOU Donghua. Review and perspectives on fault tolerant control for interconnected systems[J]. Acta Automatica Sinica, 2017, 43(1): 9-19.
[26]	ESTEBAN R, ANTONIO L, LOANNIS S, et al. Robust consensus of high-order systems under output constraints: Application to rendezvous of underactuated UAVs[J]. IEEE Transactions on Automatic Control, 2023, 68(1): 329-342.
[27]	CHANG J, SHI H, ZHU S, et al. Time cost for consensus of stochastic multiagent systems with pinning control[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(1): 94-104.
[28]	XU H, YU T, REN C, et al. Finite-time decentralized sliding mode control for interconnected systems and its application to electrical power systems: A GA-assisted design method[J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2024, 71(6): 2835-2847.
[29]	DI G S. Output stabilization of flexible spacecraft with active vibration suppression[J]. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39(3): 747-759.
[30]	VOURNAS C D, PAPADIAS B C. Power system stabilization via parameter optimization-application to the hellenic interconnected system[J]. IEEE Transactions on Power Systems, 1987, 2(3): 615-622.
[31]	SONG G, TAO G. Adaptive leader-following state consensus of multiagent systems with switching topology[J]. International Journal of Adaptive Control and Signal Processing, 2018, 32(10): 1508-1528.